Unfalsified nonlinear adaptive control

Pursues the idea that adaptive linear control can be used to nullify deleterious effects of unknown nonlinearities. A direct adaptive algorithm based on unfalsified control ideas are shown to correctly adjust a control parameter without any knowledge of the plant, which in this case is bilinear and with a linear feedback controller is easily coaxed into multi-periodic and chaotic behavior. At present no method of analysis is apparent from which one can predict the (nonlinear) systems for which this method of adaptation will likely be successful. As mentioned, averaging analysis of slowly adapting systems can be used to draw some inferences, provided the method presented is analogous to slow adaptation. It may be so, because the parameters are iteratively adjusted after accumulating a reasonable amount of data which most likely has an averaging effect